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LNOx Emission Model for Air Quality & Climate Studies Using Satellite Lightning Mapper Observations
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  • Yuling Wu,
  • Arastoo Pour Biazar,
  • William J. Koshak,
  • Peiyang Cheng
Yuling Wu
University of Alabama - Huntsville

Corresponding Author:wuy@nsstc.uah.edu

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Arastoo Pour Biazar
University of Alabama in Huntsville
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William J. Koshak
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Peiyang Cheng
University of Alabama in Huntsville
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A lightning nitrogen oxides (LNOx) emissions model using satellite-observed lightning optical energy is introduced for utilization in Air Quality modeling systems. The effort supports assessments of air-quality/climate coupling as related to the influence of LNOx on atmospheric chemistry. The Geostationary Lightning Mapper (GLM), International Space Station Lightning Imaging Sensor (ISS-LIS), and the Tropical Rainfall Measuring Mission (TRMM) LIS data are used to examine the efficacy of the method, extend the previously derived LNOx record, and demonstrate a path for using ISS-LIS observations to cross-calibrate regional LNOx estimates from the future global constellation of geostationary lightning observations. A detailed evaluation of the GLM dataset is provided to establish the robustness of observations for LNOx estimates and to make preliminary assessments of the LNOx emissions model. Seasonal and geographical variation, land/ocean contrast, and annual fluctuation in the GLM observed lightning activity and flash optical energy are provided. GLM detection substantially degrades with the increase in the field of view, resulting in 44% more flashes and 40% less optical energy observation by GLM-16 (compared to GLM-17) to the east of the middle-longitude between the two mappers (106.2°W). Regular horizontal striations are found in the optical energy product. On average, GLM flashes matched to the cloud-to-ground flashes have ~30% longer duration, 50-70% more extension, and ≥ 100% higher optical energy compared to the unmatched flashes (assumed to be intra-cloud). The results from summer-long chemical transport simulations using LNOx generated from the emission model agrees with previous studies and shows consistency across the GLM/LIS datasets.